At NVIDIA, our Financial Systems Engineering team is at the heart of ensuring that our massive scale operates with zero friction! We are responsible for architecting and operating the end-to-end financial data lifecycle, from ingestion to reporting. Our mission is to build high-speed rails for NVIDIA's revenue, ensuring transactional integrity, idempotency, and financial accuracy across distributed systems. This team is not just about IT support; we are the guardians of financial reliability and innovation, driving zero-touch automation and enabling NVIDIA to operate at peak efficiency.
What You’ll Be Doing:
Strategy & Leadership: Define the financial data platform roadmap and mentor a high-performing team of software and data engineers to foster a culture of innovation.
Architecture & Reliability: Enforce "Infrastructure as Code" principles and design scalable ETL architectures to ensure 99.999% system reliability at internet scale.
Governance & Compliance: Implement robust data governance frameworks to maintain financial data integrity and ensure strict adherence to audit and regulatory standards.
What We Need to See:
Bachelor's, Master's degree or equivalent experience in Data Engineering, Computer Science, or a related technical field
8+ overall years of experience in data processing with Hadoop and Spark. Proficient in container orchestration using Docker and Kubernetes on public cloud platforms like AWS, GCP, and Azure.
3+ years of proven experience building and managing teams, conducting performance reviews, and driving best practices for database performance and query optimization.
Technical Core: Deep technical roots in Data Engineering with expertise in Python, Airflow/Dagster, Flink, Druid, Kafka, and ERP data within cloud environments.
Financial Domain: Experience managing financial data lifecycles, including specific knowledge of audits, SOX compliance, and revenue recognition processes.
Ways to Stand Out from the Crowd:
Advanced Data Modeling: Experience developing data ontology or semantic data layers that map disparate raw data into interconnected objects with defined properties and relationships.
Global Collaboration: Demonstrated ability to drive critical initiatives across cross-functional teams and global geographies.
You will also be eligible for equity and benefits.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”







